Power-reaching-law-based sliding-mode controlled magnetic suspension train system control method

Abstract

The invention relates to a power-reaching-law-based sliding-mode controlled magnetic suspension train system control method. Based on a single magnet structure magnetic suspension system model, and onthe basis of performing linearization on the input and output relation, the power-reaching-law-based sliding-mode controlled magnetic suspension train system control method analyzes the control relation of the application of sliding-mode control of the power reaching law in the single magnet structure magnetic suspension system, and utilizes a Lyapunov stability theory to analyze the stability ofthe method. The Matlab simulation result shows that compared with traditional sliding-mode control, the sliding-mode control of the power reaching law has better control performance, and has the advantages of significantly weakening buffeting, being smaller in the positional signal error, being better in dynamic characteristic, and being higher in robustness.

Description

technical field [0001] The invention relates to a control method for a maglev train system, in particular to a control method for a maglev train system based on power reaching law sliding mode control. Background technique [0002] The maglev train system is a single-degree-of-freedom open-loop unstable nonlinear system, which is easily affected by system parameter disturbance and external disturbance, which brings difficulties to the system control. Although the conventional PID controller can make the system stable, the adaptability of the system to parameter changes is poor; therefore, Sakalli et al. use fuzzy PID for control, which is characterized by no need for an accurate system model, and the parameters can be adjusted online, which can obtain Satisfactory system dynamic performance and stability performance, but the fuzzy rules of fuzzy control can only be obtained by experience and the algorithm is more complicated; so Ulbig and others use the predictive control me...

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Problems solved by technology

[0002] The maglev train system is a single-degree-of-freedom open-loop unstable nonlinear system, which is easily affected by system parameter disturbance and external disturbance, which brings difficulties to the control of the system

Although the conventional PID controller can make the system stable, the adaptability of the system to parameter changes is poor; therefore, Sakalli et al. use fuzzy PID for control, which is characterized by no need for an accurate system model, and the parameters can be adjusted online, which can obtain Satisfactory system dynamic performance and stability performance, but the fuzzy rules of fuzzy control can only be obtained by experience and the algorithm is more complicated; so Ulbig and others use the predictive control method, because of its robustness and low requirements for model accuracy, It can effectively deal with the advantages of nonlinearity and uncertainty of the controlled object, but the disadvantage is that the amount of calculation is large; Uswarman et al. realized that the sliding mode control is not sensitive to parameter changes and disturbances, does not require online system identification, and has the advantages of simple physical implementation. Sliding mode control is used for control, but sliding mode control will have obvious chattering problems, which will cause position fluctuations of the suspended object when it reaches a steady state

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